Cargando…
Clinical data sharing improves quality measurement and patient safety
OBJECTIVE: Accurate and robust quality measurement is critical to the future of value-based care. Having incomplete information when calculating quality measures can cause inaccuracies in reported patient outcomes. This research examines how quality calculations vary when using data from an individu...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279795/ https://www.ncbi.nlm.nih.gov/pubmed/33712850 http://dx.doi.org/10.1093/jamia/ocab039 |
_version_ | 1783722518126788608 |
---|---|
author | D’Amore, John D McCrary, Laura K Denson, Jody Li, Chun Vitale, Christopher J Tokachichu, Priyaranjan Sittig, Dean F McCoy, Allison B Wright, Adam |
author_facet | D’Amore, John D McCrary, Laura K Denson, Jody Li, Chun Vitale, Christopher J Tokachichu, Priyaranjan Sittig, Dean F McCoy, Allison B Wright, Adam |
author_sort | D’Amore, John D |
collection | PubMed |
description | OBJECTIVE: Accurate and robust quality measurement is critical to the future of value-based care. Having incomplete information when calculating quality measures can cause inaccuracies in reported patient outcomes. This research examines how quality calculations vary when using data from an individual electronic health record (EHR) and longitudinal data from a health information exchange (HIE) operating as a multisource registry for quality measurement. MATERIALS AND METHODS: Data were sampled from 53 healthcare organizations in 2018. Organizations represented both ambulatory care practices and health systems participating in the state of Kansas HIE. Fourteen ambulatory quality measures for 5300 patients were calculated using the data from an individual EHR source and contrasted to calculations when HIE data were added to locally recorded data. RESULTS: A total of 79% of patients received care at more than 1 facility during the 2018 calendar year. A total of 12 994 applicable quality measure calculations were compared using data from the originating organization vs longitudinal data from the HIE. A total of 15% of all quality measure calculations changed (P < .001) when including HIE data sources, affecting 19% of patients. Changes in quality measure calculations were observed across measures and organizations. DISCUSSION: These results demonstrate that quality measures calculated using single-site EHR data may be limited by incomplete information. Effective data sharing significantly changes quality calculations, which affect healthcare payments, patient safety, and care quality. CONCLUSIONS: Federal, state, and commercial programs that use quality measurement as part of reimbursement could promote more accurate and representative quality measurement through methods that increase clinical data sharing. |
format | Online Article Text |
id | pubmed-8279795 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82797952021-07-15 Clinical data sharing improves quality measurement and patient safety D’Amore, John D McCrary, Laura K Denson, Jody Li, Chun Vitale, Christopher J Tokachichu, Priyaranjan Sittig, Dean F McCoy, Allison B Wright, Adam J Am Med Inform Assoc Research and Applications OBJECTIVE: Accurate and robust quality measurement is critical to the future of value-based care. Having incomplete information when calculating quality measures can cause inaccuracies in reported patient outcomes. This research examines how quality calculations vary when using data from an individual electronic health record (EHR) and longitudinal data from a health information exchange (HIE) operating as a multisource registry for quality measurement. MATERIALS AND METHODS: Data were sampled from 53 healthcare organizations in 2018. Organizations represented both ambulatory care practices and health systems participating in the state of Kansas HIE. Fourteen ambulatory quality measures for 5300 patients were calculated using the data from an individual EHR source and contrasted to calculations when HIE data were added to locally recorded data. RESULTS: A total of 79% of patients received care at more than 1 facility during the 2018 calendar year. A total of 12 994 applicable quality measure calculations were compared using data from the originating organization vs longitudinal data from the HIE. A total of 15% of all quality measure calculations changed (P < .001) when including HIE data sources, affecting 19% of patients. Changes in quality measure calculations were observed across measures and organizations. DISCUSSION: These results demonstrate that quality measures calculated using single-site EHR data may be limited by incomplete information. Effective data sharing significantly changes quality calculations, which affect healthcare payments, patient safety, and care quality. CONCLUSIONS: Federal, state, and commercial programs that use quality measurement as part of reimbursement could promote more accurate and representative quality measurement through methods that increase clinical data sharing. Oxford University Press 2021-03-13 /pmc/articles/PMC8279795/ /pubmed/33712850 http://dx.doi.org/10.1093/jamia/ocab039 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permitsunrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research and Applications D’Amore, John D McCrary, Laura K Denson, Jody Li, Chun Vitale, Christopher J Tokachichu, Priyaranjan Sittig, Dean F McCoy, Allison B Wright, Adam Clinical data sharing improves quality measurement and patient safety |
title | Clinical data sharing improves quality measurement and patient safety |
title_full | Clinical data sharing improves quality measurement and patient safety |
title_fullStr | Clinical data sharing improves quality measurement and patient safety |
title_full_unstemmed | Clinical data sharing improves quality measurement and patient safety |
title_short | Clinical data sharing improves quality measurement and patient safety |
title_sort | clinical data sharing improves quality measurement and patient safety |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279795/ https://www.ncbi.nlm.nih.gov/pubmed/33712850 http://dx.doi.org/10.1093/jamia/ocab039 |
work_keys_str_mv | AT damorejohnd clinicaldatasharingimprovesqualitymeasurementandpatientsafety AT mccrarylaurak clinicaldatasharingimprovesqualitymeasurementandpatientsafety AT densonjody clinicaldatasharingimprovesqualitymeasurementandpatientsafety AT lichun clinicaldatasharingimprovesqualitymeasurementandpatientsafety AT vitalechristopherj clinicaldatasharingimprovesqualitymeasurementandpatientsafety AT tokachichupriyaranjan clinicaldatasharingimprovesqualitymeasurementandpatientsafety AT sittigdeanf clinicaldatasharingimprovesqualitymeasurementandpatientsafety AT mccoyallisonb clinicaldatasharingimprovesqualitymeasurementandpatientsafety AT wrightadam clinicaldatasharingimprovesqualitymeasurementandpatientsafety |